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•Converting clinical terms into SNOMED CT concepts is desirable for many applications.•Automated method is presented for conversion, including to post-coordinated concepts.•The method ...identifies defining relations of the concept expressed by a clinical term.•It is trained using existing SNOMED CT and does not need extra manual annotations.•Evaluation is done using terms from SNOMED CT and terms found in clinical text.
SNOMED CT is the most comprehensive clinical ontology and is also amenable for automated reasoning. However, in order to unleash its full potential for automated reasoning over clinical text, a mechanism to convert clinical terms into SNOMED CT concepts is necessary. In this paper we present, to the best of our knowledge, the first such complete conversion method that is also capable of converting clinical terms into post-coordinated concepts which are not already listed in SNOMED CT. The method does not require any additional manual annotations and learns only from existing SNOMED CT terms paired with their concepts. The method is based on identifying the defining relations of the clinical concept expressed by a clinical term. We evaluate our method on a large-scale using existing data from SNOMED CT as well as on a small-scale using manually annotated dataset of clinical terms found in clinical text.
•Riemann and delta-shock solutions for a non symmetric Keyfitz-Kranzer (NSKK) system.•Mathematical comprehension of Coulomb friction term/linear damping for NSKK system.•An improved ...Lagrangian-Eulerian scheme for NSKK system with source term.•Improvement of mathematical analysis of delta-shock as solutions for NSKK systems.•Analytical and numerical examples for verifying the theory/capabilities of method.
In this work, we study Riemann problems and delta-shock solutions for a nonsymmetric Keyfitz-Kranzer system with a Coulomb-like friction term or linear damping. We show the existence of an intricate delta-shock wave solution and its generalized Rankine-Hugoniot condition resulting from the analysis. In particular, we also show the existence of a shock wave solution satisfying the classical Rankine-Hugoniot condition and the Lax shock condition, which is supported by the corresponding homogeneous Keyfitz-Kranzer system under investigation. Some numerical results exhibiting the formation process of delta-shocks are also presented, verifying the theory being presented. In particular, the robustness of the numerics is illustrated with a very interesting linear damping example, where we show a simulation of the cutoff time in which a delta-shock singular solution ceases to exist, and in fully agreement with the theoretical results.
•The controller designed is delay-independent, which is feasible whether the time delay is known or not.•Unlike earlier works, the activation functions need to satisfy the Lipschitz condi- tion, we ...only require that the activation functions be bounded.•The controller designed in this paper can be applied to obtain the new criterion of FTS.•The ST can be calculated and a tighter value under the same conditions compared with the common criteria of FTS is obtained.
The problem of fixed-time synchronization (FTS) control for memristive neural networks (MNNs) with discrete timedelay and inertia term is investigated in this work. Firstly, delayed inertial memristive neural networks (DIMNNs) are characterized as the differential equations, which is second-order and has discontinuous right-hand side. Secondly, a suitable two-parameter variable substitution method is advocated for the second-order derivatives of states, and then DIMNNs can be represented in the shape of first-order differential equation. Thirdly, a new fixed-time criterion and FTS of DIMNNs are achieved under the designed feedback controller in the light of comparison lemma and inequality techniques. Meanwhile, the settling-time (ST) of FTS is estimated, it could be adjusted to arbitrary expected values by controller parameters without relying on the initial conditions and also fully reflects that a tighter ST value is obtained. Finally, the effectiveness of the brought forward theoretical results is testified via a numerical simulation.
We study the existence of distributional solutions for the boundary value problems (1.1) and (1.2) if E does not belong to LN, namely |E|≤|A||x|, A∈R. The size of A plays an important role: if ...α(N−2)≤|A|<α(N−1), we prove that if f∈L1(Ω) there exists a distributional solution u∈W01,q(Ω), for every q<Nα|A|+α<NN−1, of (1.1) (the case |A|<α(N−2) is studied in Boccardo (2015)). We then use this result to prove the existence of a bounded weak solution ψ of (1.2) if g(x)∈Lm(Ω), m>NαNα−|A|≥N2.
We proposed a provably stable FDTD subgridding method for accurate and efficient transient electromagnetic analysis. In the proposed method, several field components are properly added to the ...boundaries of Yee's grid to make sure that the discrete operators meet the 2nd-order and 4th-order summation-by-parts (SBP) properties. Then, by incorporating the simultaneous approximation terms (SATs) into the finite-difference time-domain (FDTD) method, the proposed FDTD subgridding method mimics the energy estimate of the continuous Maxwell's equations at the semi-discrete level to guarantee its stability. Furthermore, to couple multiple mesh blocks with different mesh sizes, the interpolation matrices are also derived. The proposed FDTD subgridding method is accurate, efficient, easy to implement and integrate into the existing FDTD codes with only simple modifications. At last, four numerical examples with fine structures are carried out to validate the effectiveness of the proposed method.
•A SBP-SAT FDTD subgridding technique is proposed to solve TM electromagnetic problems.•A few additional field components are added on the boundaries of Yee's cell to make operators meet the SBP properties.•The proposed subgridding technique is theoretically stable.•Interpolation matrices between coarse and fine mesh blocks are detailed derived to guarantee the stability and accuracy.
Neutrophils: Friend or foe in Filariasis? Ajendra, Jesuthas; Allen, Judith E.
Parasite immunology,
June 2022, 2022-Jun, 2022-06-00, 20220601, Volume:
44, Issue:
6
Journal Article
Peer reviewed
Infection with the filarial nematodes that cause diseases such as lymphatic filariasis and onchocerciasis represent major public health challenges. With millions of people at risk of infection, new ...strategies for treatment or prevention are urgently needed. More complete understanding of the host immune system's ability to control and eliminate the infection is an important step towards fighting these debilitating infectious diseases. Neutrophils are innate immune cells that are rapidly recruited to inflamed or infected tissues and while considered primarily anti‐microbial, there is increasing recognition of their role in helminth infections. Filarial nematodes present a unique situation, as many species harbour the bacterial endosymbiont, Wolbachia. The unexpected involvement of neutrophils during filarial infections has been revealed both in human diseases and animal studies, with strong evidence for recruitment by Wolbachia. This present review will introduce the different human filarial diseases and discuss neutrophil involvement in both protective immune responses, but also in the exacerbation of pathology. Additionally, we will highlight the contributions of the murine model of filariasis, Litomosoides sigmodontis. While several studies have revealed the importance of neutrophils in these parasite infections, we will also draw attention to many questions that remain to be answered.
In this study, we compared two experimental methods of selecting terms in expository text to generate reading representations and tested how well these reading representations predicted reading ...comprehension. The two experimental methods were the traditional method of using all terms (all keywords) to create participants' representation networks, and the terms categorization (TC) method of using only important terms (core and branch words). Representation networks were assessed using participants' adjacency scores, ratings of relatedness in pairs of terms, and using summary (summary writing) by all turms. An in-subject design was performed in experiments 1 and 2, and an inter-subject design was performed in experiment 3 to test the hypothesis. With the same sample in exp1 and epx2, a different sample in each exp3. Experiment 1 showed that when using only the traditional way of selecting terms, adjacency was better than relatedness in predicting reading comprehension. Reading representations generated based on the summary method could not predict participants' reading comprehension ability, so this method was excluded from subsequent studies. Experiment 2 showed that the terms selected in Experiment 1 were stronger predictors of reading comprehension when the word pairs included a core term (central to understanding of full text) or a branch term (key to understanding paragraph), relative to a detail term (not affect the understanding full text). Experiment 3 found that whereas the two methods were equally effective in generating representations measured by adjacency, TC was superior in generating representations measured by relatedness. These conclusions have important implications for future research and application.
Large errors in flu prediction were largely avoidable, which offers lessons for the use of big data.
In February 2013, Google Flu Trends (GFT) made headlines but not for a reason that Google ...executives or the creators of the flu tracking system would have hoped.
Nature
reported that GFT was predicting more than double the proportion of doctor visits for influenza-like illness (ILI) than the Centers for Disease Control and Prevention (CDC), which bases its estimates on surveillance reports from laboratories across the United States (
1
,
2
). This happened despite the fact that GFT was built to predict CDC reports. Given that GFT is often held up as an exemplary use of big data (
3
,
4
), what lessons can we draw from this error?
The traditional Wigner distribution (WD) is extended to a novel one inspired by the definition of fractional bispectrum, giving rise to a scaled version with respect to the frequency variable, termed ...as the scaled Wigner distribution (SWD). A natural magnification effect characterized by a factor k on the frequency axis enables the SWD to have flexibility to be used in cross-term reduction. Some essential properties of this variation generalize very nicely and simply the classical results for the WD, and it enjoys a computational complexity in the order of O(kN2) comparable to O(N2) of the WD. The SWD does not use localization windows, but its resolutions depend on the factor k. Comparison of the detection performance (i.e. cross-term reduction, time–frequency resolution, angle or distance resolution) of SWD and WD for multicomponent linear frequency-modulated (LFM) signals processing is then observed by exploring the factor k selection results on two kinds of bi-component cases, including the one with a different frequency rate and the other one with the same frequency rate but having a different initial frequency. Correctness of the derived results and the SWD’s superiority in the instantaneous frequency estimation of noisy LFM signals compared with the WD are illustrated through simulations, and finally further discussions point out some promising future research directions and perspectives.
Up to 8% of the general population have a rare disease, however, for lack of ICD-10 codes for many rare diseases, this population cannot be generically identified in large medical datasets. We aimed ...to explore frequency-based rare diagnoses (FB-RDx) as a novel method exploring rare diseases by comparing characteristics and outcomes of inpatient populations with FB-RDx to those with rare diseases based on a previously published reference list.
Retrospective, cross-sectional, nationwide, multicenter study including 830,114 adult inpatients. We used the national inpatient cohort dataset of the year 2018 provided by the Swiss Federal Statistical Office, which routinely collects data from all inpatients treated in any Swiss hospital. Exposure: FB-RDx, according to 10% of inpatients with the least frequent diagnoses (i.e.1.decile) vs. those with more frequent diagnoses (deciles 2-10). Results were compared to patients having 1 of 628 ICD-10 coded rare diseases.
In-hospital death.
30-day readmission, admission to intensive care unit (ICU), length of stay, and ICU length of stay. Multivariable regression analyzed associations of FB-RDx and rare diseases with these outcomes.
464,968 (56%) of patients were female, median age was 59 years (IQR: 40-74). Compared with patients in deciles 2-10, patients in the 1. were at increased risk of in-hospital death (OR 1.44; 95% CI: 1.38, 1.50), 30-day readmission (OR 1.29; 95% CI 1.25, 1.34), ICU admission (OR 1.50; 95% CI 1.46, 1.54), increased length of stay (Exp(B) 1.03; 95% CI 1.03, 1.04) and ICU length of stay (1.15; 95% CI 1.12, 1.18). ICD-10 based rare diseases groups showed similar results: in-hospital death (OR 1.82; 95% CI 1.75, 1.89), 30-day readmission (OR 1.37; 95% CI 1.32, 1.42), ICU admission (OR 1.40; 95% CI 1.36, 1.44) and increased length of stay (OR 1.07; 95% CI 1.07, 1.08) and ICU length of stay (OR 1.19; 95% CI 1.16, 1.22).
This study suggests that FB-RDx may not only act as a surrogate for rare diseases but may also help to identify patients with rare disease more comprehensively. FB-RDx associate with in-hospital death, 30-day readmission, intensive care unit admission, and increased length of stay and intensive care unit length of stay, as has been reported for rare diseases.
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